Principal Engineer, AI Retrieval & Knowledge Platforms

LPL Financial

Confirmed live yesterday High trust

Quick summary

Work type
On-site
Location
Fort Mill, SCCharlotte, NCNew York, NYAustin, TX
Employment
Full-time
Posted
48 days ago
Freshness
Confirmed live yesterday
Nearby
99+ roles within 25 mi

Market check

Salary context

How this pay compares to similar roles

Similar $217k
$136k $279k
below market most similar roles pay here above market

This listing doesn't post a salary. Most similar roles pay $169,550–$265,250.

Based on 240 similar postings.

Employer

About LPL Financial

LPL Financial is the largest independent broker-dealer in the United States, providing brokerage and investment advisory services to independent financial advisors and financial institutions. Industry: Financial Services & Wealth Management

LPL Financial currently has 100 open roles on FindRole.

Listed pay typically runs $127,100–$211,900 across 55 roles with salary data.

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At a glance

TL;DR · Principal Engineer, AI Retrieval & Knowledge Platforms

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The Principal Engineer, AI Retrieval & Knowledge Platforms will design and build core AI knowledge infrastructure to power intelligent applications across the enterprise. Working on distributed systems and retrieval architectures, you will develop high-performance platforms for search, vector retrieval, and LLMs. Key responsibilities include building RAG infrastructure, indexing pipelines for structured and unstructured data, and low-latency APIs for AI agents. You will implement semantic search, vector stores, and hybrid retrieval systems while managing streaming data via Kafka. Required technical skills include Java, Python, or Go, along with experience in Kubernetes, CI/CD, and microservices. The role solves the technical challenge of enabling applications to discover and reason over large-scale enterprise data within highly regulated environments like wealth management, banking, and capital markets.

What does a Engineer earn in New York?

Median $200000 from 37 postings across 15 companies.

See salary data

Skills

RAG Vector Databases LLM Python Java Go Kubernetes Kafka Elasticsearch OpenSearch CI/CD Distributed Systems Semantic Search Embeddings Microservices Infrastructure-as-Code Observability Streaming Systems APIs Containers

What you'll do

  • Design and build high-scale retrieval systems combining keyword, semantic, and vector-based search.
  • Develop RAG infrastructure including indexing, retrieval, ranking, and context assembly.
  • Build streaming and batch pipelines for ingesting and transforming structured and unstructured data.
  • Create low-latency, highly available APIs and reusable SDKs for retrieval and knowledge services.
  • Integrate LLMs with retrieval systems to enable grounded, context-aware experiences and response orchestration.
  • Implement observability pipelines for metrics, logs, and tracing to monitor system performance.
  • Lead the architecture of large-scale AI platform components and mentor engineers on retrieval practices.

What we're looking for

  • Minimum of 8 years of experience building large-scale backend, platform, or distributed systems.
  • Hands-on experience building search platforms, retrieval systems, indexing pipelines, knowledge systems, or recommendation platforms.
  • Proficiency in programming with Java, Python, or Go.
  • Strong knowledge of APIs, microservices, Kubernetes, containers, CI/CD, and distributed data processing.
  • Experience building enterprise platforms in highly regulated environments such as Wealth Management, Banking, FinTech, or Healthcare.
  • Experience building AI platforms, copilots, or agent-based systems (preferred).
  • Experience with Elasticsearch/OpenSearch, vector databases, or hybrid retrieval architectures (preferred).
  • Experience with real-time data systems like Kafka or streaming pipelines (preferred).

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